This paper presents an interference suppression and signal restoration technique that can create the clean signals required by automotive frequency-modulated continuous wave radar systems. When a radar signal from another radar system interferes with own transmitted radar signal, the target detection performance is degraded. This is because the beat frequency corresponding to the target cannot be estimated owing to the increase in the noise floor. In this case, advanced weighted-envelope normalization or wavelet denoising can be used to mitigate the effect of the interference; however, these methods can also lead to the loss of the desired signal containing the range and velocity information of the target. Therefore, we propose a method based on an autoregressive model to restore a signal damaged by mutual interference. The method uses signals that are not influenced by the interference to restore the signal. In experiments conducted using two different automotive radar systems, our proposed method is demonstrated to effectively suppress the interference and restore the desired signal. As a result, the noise floor resulting from the mutual interference was lowered and the beat frequency corresponding to the desired target was accurately estimated.

With extensive use of automotive radars, mutual interference between radars has become a crucial issue, since it increases the noise floor in the frequency domain triggering frequent false alarms and unsafe decision. This paper introduces a mathematical model for a frequency-modulated continuous-wave (FMCW) radar in interfering environments. In addition, this paper proposes a time-domain interference suppression method to provide anti-interference capability regardless of the signal-to-interference ratio. Numerical results are presented to verify the performance of a 77GHz FMCW radar systme with the proposed method in interference-rich environments.